Overview

Dataset statistics

Number of variables14
Number of observations52704
Missing cells7758
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 MiB
Average record size in memory112.0 B

Variable types

DateTime1
Numeric13

Alerts

Power (kW) is highly overall correlated with Rear bearing temperature (°C) and 6 other fieldsHigh correlation
Wind direction (°) is highly overall correlated with Nacelle position (°)High correlation
Nacelle position (°) is highly overall correlated with Wind direction (°)High correlation
blade_angle is highly overall correlated with Rear bearing temperature (°C)High correlation
Rear bearing temperature (°C) is highly overall correlated with Power (kW) and 5 other fieldsHigh correlation
Rotor speed (RPM) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Generator RPM (RPM) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Front bearing temperature (°C) is highly overall correlated with Power (kW) and 5 other fieldsHigh correlation
Tower Acceleration X (mm/ss) is highly overall correlated with Power (kW) and 4 other fieldsHigh correlation
Wind speed (m/s) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Tower Acceleration y (mm/ss) is highly overall correlated with Power (kW) and 5 other fieldsHigh correlation
blade_angle has 714 (1.4%) missing valuesMissing
Rear bearing temperature (°C) has 714 (1.4%) missing valuesMissing
Nacelle ambient temperature (°C) has 714 (1.4%) missing valuesMissing
Front bearing temperature (°C) has 714 (1.4%) missing valuesMissing
Tower Acceleration X (mm/ss) has 714 (1.4%) missing valuesMissing
Tower Acceleration y (mm/ss) has 714 (1.4%) missing valuesMissing
Metal particle count counter has 714 (1.4%) missing valuesMissing
# Date and time has unique valuesUnique
blade_angle has 22814 (43.3%) zerosZeros
Rotor speed (RPM) has 1478 (2.8%) zerosZeros

Reproduction

Analysis started2023-07-08 11:59:00.824238
Analysis finished2023-07-08 11:59:18.493466
Duration17.67 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

Distinct52704
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size411.9 KiB
Minimum2020-01-01 00:00:00
Maximum2020-12-31 23:50:00
2023-07-08T17:29:18.540397image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:18.636674image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Power (kW)
Real number (ℝ)

Distinct52212
Distinct (%)99.9%
Missing460
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean722.01646
Minimum-16.486462
Maximum2082.6398
Zeros3
Zeros (%)< 0.1%
Negative5329
Negative (%)10.1%
Memory size411.9 KiB
2023-07-08T17:29:18.739313image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-16.486462
5-th percentile-1.1166155
Q1139.74096
median492.38931
Q31204.0996
95-th percentile2030.8517
Maximum2082.6398
Range2099.1262
Interquartile range (IQR)1064.3586

Descriptive statistics

Standard deviation680.97523
Coefficient of variation (CV)0.94315748
Kurtosis-0.81521442
Mean722.01646
Median Absolute Deviation (MAD)424.54088
Skewness0.74206364
Sum37721028
Variance463727.26
MonotonicityNot monotonic
2023-07-08T17:29:18.833575image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.8162550241 3
 
< 0.1%
-0.1045660032 3
 
< 0.1%
0 3
 
< 0.1%
164.7899933 2
 
< 0.1%
-0.08589350265 2
 
< 0.1%
-0.8733395249 2
 
< 0.1%
-0.7623715222 2
 
< 0.1%
-0.2107325073 2
 
< 0.1%
330.0305359 2
 
< 0.1%
-1.134754533 2
 
< 0.1%
Other values (52202) 52221
99.1%
(Missing) 460
 
0.9%
ValueCountFrequency (%)
-16.48646166 1
< 0.1%
-16.4711801 1
< 0.1%
-15.42775617 1
< 0.1%
-15.13105168 1
< 0.1%
-15.04848154 1
< 0.1%
-15.01627111 1
< 0.1%
-14.40552152 1
< 0.1%
-14.29930916 1
< 0.1%
-14.16668259 1
< 0.1%
-12.96018654 1
< 0.1%
ValueCountFrequency (%)
2082.639758 1
< 0.1%
2076.614417 1
< 0.1%
2076.289008 1
< 0.1%
2075.82265 1
< 0.1%
2074.964208 1
< 0.1%
2074.818567 1
< 0.1%
2074.735858 1
< 0.1%
2073.992676 1
< 0.1%
2073.857697 1
< 0.1%
2072.207996 1
< 0.1%

Wind direction (°)
Real number (ℝ)

Distinct52243
Distinct (%)> 99.9%
Missing460
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean197.22441
Minimum0.0099930291
Maximum359.99365
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:29:18.927357image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.0099930291
5-th percentile28.804793
Q1142.32276
median216.43149
Q3257.93578
95-th percentile325.57861
Maximum359.99365
Range359.98366
Interquartile range (IQR)115.61302

Descriptive statistics

Standard deviation91.448554
Coefficient of variation (CV)0.46367768
Kurtosis-0.66290806
Mean197.22441
Median Absolute Deviation (MAD)49.996697
Skewness-0.53599187
Sum10303792
Variance8362.8381
MonotonicityNot monotonic
2023-07-08T17:29:19.023809image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
302.6900024 2
 
< 0.1%
113.7778434 1
 
< 0.1%
351.534435 1
 
< 0.1%
50.35263643 1
 
< 0.1%
351.7332237 1
 
< 0.1%
359.5652353 1
 
< 0.1%
243.7811645 1
 
< 0.1%
252.6678813 1
 
< 0.1%
286.1880912 1
 
< 0.1%
159.8713604 1
 
< 0.1%
Other values (52233) 52233
99.1%
(Missing) 460
 
0.9%
ValueCountFrequency (%)
0.009993029124 1
< 0.1%
0.03828162361 1
< 0.1%
0.04563247687 1
< 0.1%
0.04723364604 1
< 0.1%
0.05011688289 1
< 0.1%
0.05337678726 1
< 0.1%
0.06762437105 1
< 0.1%
0.1005209211 1
< 0.1%
0.1536742368 1
< 0.1%
0.1542169302 1
< 0.1%
ValueCountFrequency (%)
359.9936545 1
< 0.1%
359.9775761 1
< 0.1%
359.9317122 1
< 0.1%
359.9204816 1
< 0.1%
359.9185786 1
< 0.1%
359.8877918 1
< 0.1%
359.8749538 1
< 0.1%
359.8703891 1
< 0.1%
359.8444897 1
< 0.1%
359.8015379 1
< 0.1%

Nacelle position (°)
Real number (ℝ)

Distinct11804
Distinct (%)22.6%
Missing460
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean198.1094
Minimum0.020981238
Maximum359.84991
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:29:19.127500image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.020981238
5-th percentile29.151216
Q1144.43903
median217.97638
Q3258.58627
95-th percentile325.53772
Maximum359.84991
Range359.82893
Interquartile range (IQR)114.14725

Descriptive statistics

Standard deviation91.777068
Coefficient of variation (CV)0.46326459
Kurtosis-0.65162922
Mean198.1094
Median Absolute Deviation (MAD)49.686242
Skewness-0.54288046
Sum10350027
Variance8423.0302
MonotonicityNot monotonic
2023-07-08T17:29:19.223769image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
241.025238 238
 
0.5%
250.9033203 232
 
0.4%
248.7081909 217
 
0.4%
314.5620728 217
 
0.4%
322.2450256 213
 
0.4%
245.4154968 211
 
0.4%
36.87928391 211
 
0.4%
267.3667908 206
 
0.4%
237.7325439 196
 
0.4%
249.8057556 196
 
0.4%
Other values (11794) 50107
95.1%
(Missing) 460
 
0.9%
ValueCountFrequency (%)
0.02098123788 1
< 0.1%
0.08035518449 1
< 0.1%
0.3090382042 1
< 0.1%
0.3321603262 1
< 0.1%
0.3652644235 1
< 0.1%
0.3689584505 1
< 0.1%
0.4825988371 1
< 0.1%
0.5501151855 1
< 0.1%
0.590251353 1
< 0.1%
0.6117708693 1
< 0.1%
ValueCountFrequency (%)
359.8499075 1
 
< 0.1%
359.7551987 1
 
< 0.1%
359.7167625 1
 
< 0.1%
359.6118061 1
 
< 0.1%
359.5622253 41
0.1%
359.5617065 27
0.1%
359.5611877 8
 
< 0.1%
359.4248401 1
 
< 0.1%
359.2335756 1
 
< 0.1%
359.2021638 1
 
< 0.1%

blade_angle
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct21677
Distinct (%)41.7%
Missing714
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean6.6759129
Minimum0
Maximum92.489998
Zeros22814
Zeros (%)43.3%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:29:19.326738image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.050333203
Q31.5232356
95-th percentile44.993334
Maximum92.489998
Range92.489998
Interquartile range (IQR)1.5232356

Descriptive statistics

Standard deviation17.857214
Coefficient of variation (CV)2.6748722
Kurtosis11.401704
Mean6.6759129
Median Absolute Deviation (MAD)0.050333203
Skewness3.3758041
Sum347080.71
Variance318.88009
MonotonicityNot monotonic
2023-07-08T17:29:19.420603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22814
43.3%
44.99333445 1442
 
2.7%
44.99000168 1109
 
2.1%
89.98999786 765
 
1.5%
92.40333303 270
 
0.5%
0.02450000048 249
 
0.5%
44.99666723 216
 
0.4%
1.49333334 191
 
0.4%
0.02466666698 189
 
0.4%
0.02449974513 117
 
0.2%
Other values (21667) 24628
46.7%
(Missing) 714
 
1.4%
ValueCountFrequency (%)
0 22814
43.3%
0.0001666666622 12
 
< 0.1%
0.0001666666629 21
 
< 0.1%
0.0001754385926 5
 
< 0.1%
0.000185185181 1
 
< 0.1%
0.000196078427 1
 
< 0.1%
0.0002222222163 1
 
< 0.1%
0.0002222222173 1
 
< 0.1%
0.0003333333201 4
 
< 0.1%
0.0003333333244 4
 
< 0.1%
ValueCountFrequency (%)
92.48999786 40
 
0.1%
92.45799802 1
 
< 0.1%
92.42666626 1
 
< 0.1%
92.42666626 1
 
< 0.1%
92.42333476 2
 
< 0.1%
92.42333476 1
 
< 0.1%
92.42333476 1
 
< 0.1%
92.40333303 270
0.5%
92.31455927 1
 
< 0.1%
92.30166791 1
 
< 0.1%

Rear bearing temperature (°C)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct39257
Distinct (%)75.5%
Missing714
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean64.701587
Minimum9.2575
Maximum78.599999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:29:19.517312image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum9.2575
5-th percentile41.660376
Q164.3875
median68.1625
Q370.3025
95-th percentile72.5125
Maximum78.599999
Range69.342499
Interquartile range (IQR)5.9149997

Descriptive statistics

Standard deviation10.674597
Coefficient of variation (CV)0.164982
Kurtosis9.3205589
Mean64.701587
Median Absolute Deviation (MAD)2.5350004
Skewness-2.8831238
Sum3363835.5
Variance113.94703
MonotonicityNot monotonic
2023-07-08T17:29:19.611881image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70.89250031 10
 
< 0.1%
69.4875 10
 
< 0.1%
70.82250023 10
 
< 0.1%
68.99500008 10
 
< 0.1%
69.25999985 9
 
< 0.1%
68.37000008 9
 
< 0.1%
68.99000015 9
 
< 0.1%
67.76500015 9
 
< 0.1%
71.20750008 9
 
< 0.1%
71.5625 9
 
< 0.1%
Other values (39247) 51896
98.5%
(Missing) 714
 
1.4%
ValueCountFrequency (%)
9.257500029 1
< 0.1%
9.265000057 1
< 0.1%
9.324999952 1
< 0.1%
9.405000067 1
< 0.1%
9.420000029 1
< 0.1%
9.445000172 1
< 0.1%
9.447500134 1
< 0.1%
9.455000019 1
< 0.1%
9.500000048 1
< 0.1%
9.520000124 1
< 0.1%
ValueCountFrequency (%)
78.59999886 1
< 0.1%
78.16750031 1
< 0.1%
77.94736882 1
< 0.1%
76.80500031 1
< 0.1%
76.69500084 1
< 0.1%
76.55789466 1
< 0.1%
76.33250046 1
< 0.1%
76.00500145 1
< 0.1%
75.75526268 1
< 0.1%
75.50263134 1
< 0.1%

Rotor speed (RPM)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50553
Distinct (%)96.8%
Missing460
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean10.793786
Minimum0
Maximum15.349929
Zeros1478
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:29:19.715483image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.37165126
Q18.3888395
median11.500876
Q314.66703
95-th percentile15.167932
Maximum15.349929
Range15.349929
Interquartile range (IQR)6.2781909

Descriptive statistics

Standard deviation4.2473036
Coefficient of variation (CV)0.39349528
Kurtosis0.67437754
Mean10.793786
Median Absolute Deviation (MAD)3.1373257
Skewness-1.1067874
Sum563910.53
Variance18.039588
MonotonicityNot monotonic
2023-07-08T17:29:19.813342image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1478
 
2.8%
8.140000343 39
 
0.1%
0.0110000018 16
 
< 0.1%
15.14999962 15
 
< 0.1%
15.15999985 15
 
< 0.1%
0.01200000197 12
 
< 0.1%
0.01150000188 12
 
< 0.1%
0.01050000242 9
 
< 0.1%
8.170000076 6
 
< 0.1%
0.01500000246 6
 
< 0.1%
Other values (50543) 50636
96.1%
(Missing) 460
 
0.9%
ValueCountFrequency (%)
0 1478
2.8%
0.0003120000401 1
 
< 0.1%
0.0009680002404 1
 
< 0.1%
0.00100050011 1
 
< 0.1%
0.001633500215 1
 
< 0.1%
0.005738500971 1
 
< 0.1%
0.006282223621 1
 
< 0.1%
0.006545001233 1
 
< 0.1%
0.01045200136 1
 
< 0.1%
0.01050000242 9
 
< 0.1%
ValueCountFrequency (%)
15.34992903 1
< 0.1%
15.31047495 1
< 0.1%
15.31043811 1
< 0.1%
15.30851224 1
< 0.1%
15.30158508 1
< 0.1%
15.29611981 1
< 0.1%
15.28833921 1
< 0.1%
15.28772284 1
< 0.1%
15.28707008 1
< 0.1%
15.28538454 1
< 0.1%

Generator RPM (RPM)
Real number (ℝ)

Distinct52218
Distinct (%)> 99.9%
Missing460
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean1276.927
Minimum-83.981387
Maximum1813.5739
Zeros2
Zeros (%)< 0.1%
Negative1175
Negative (%)2.2%
Memory size411.9 KiB
2023-07-08T17:29:19.918102image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-83.981387
5-th percentile43.267708
Q1993.2608
median1360.4855
Q31734.291
95-th percentile1793.8891
Maximum1813.5739
Range1897.5553
Interquartile range (IQR)741.03018

Descriptive statistics

Standard deviation502.13627
Coefficient of variation (CV)0.39323805
Kurtosis0.6851852
Mean1276.927
Median Absolute Deviation (MAD)370.34486
Skewness-1.1113662
Sum66711773
Variance252140.83
MonotonicityNot monotonic
2023-07-08T17:29:20.011580image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
970.1599731 3
 
< 0.1%
970.0300293 3
 
< 0.1%
969.9500122 3
 
< 0.1%
969.9400024 3
 
< 0.1%
970.0599976 2
 
< 0.1%
1794.283178 2
 
< 0.1%
1801.119995 2
 
< 0.1%
1788.674618 2
 
< 0.1%
1799.579956 2
 
< 0.1%
1754.272448 2
 
< 0.1%
Other values (52208) 52220
99.1%
(Missing) 460
 
0.9%
ValueCountFrequency (%)
-83.98138728 1
< 0.1%
-13.4200401 1
< 0.1%
-1.87472233 1
< 0.1%
-1.872748224 1
< 0.1%
-1.853182331 1
< 0.1%
-1.834691254 1
< 0.1%
-1.823698013 1
< 0.1%
-1.816222116 1
< 0.1%
-1.815980824 1
< 0.1%
-1.814489236 1
< 0.1%
ValueCountFrequency (%)
1813.573883 1
< 0.1%
1812.888805 1
< 0.1%
1812.295647 1
< 0.1%
1810.822781 1
< 0.1%
1809.611423 1
< 0.1%
1809.126686 1
< 0.1%
1808.964404 1
< 0.1%
1808.687525 1
< 0.1%
1808.335585 1
< 0.1%
1808.187046 1
< 0.1%
Distinct38858
Distinct (%)74.7%
Missing714
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean11.808747
Minimum-2.2399999
Maximum35.8475
Zeros0
Zeros (%)0.0%
Negative225
Negative (%)0.4%
Memory size411.9 KiB
2023-07-08T17:29:20.115239image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-2.2399999
5-th percentile3.7325
Q17.453125
median11.13204
Q315.6925
95-th percentile22.11
Maximum35.8475
Range38.0875
Interquartile range (IQR)8.239375

Descriptive statistics

Standard deviation5.7467426
Coefficient of variation (CV)0.48665137
Kurtosis0.13069303
Mean11.808747
Median Absolute Deviation (MAD)4.0475001
Skewness0.52496617
Sum613936.73
Variance33.025051
MonotonicityNot monotonic
2023-07-08T17:29:20.211247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 66
 
0.1%
9.5 52
 
0.1%
10 50
 
0.1%
7 49
 
0.1%
10.19999981 47
 
0.1%
9.899999619 46
 
0.1%
10.69999981 44
 
0.1%
9 43
 
0.1%
7.099999905 41
 
0.1%
12 41
 
0.1%
Other values (38848) 51511
97.7%
(Missing) 714
 
1.4%
ValueCountFrequency (%)
-2.239999938 1
< 0.1%
-2.234999931 1
< 0.1%
-2.164999932 1
< 0.1%
-2.149999893 1
< 0.1%
-2.119999909 1
< 0.1%
-2.109999907 1
< 0.1%
-2.105263058 1
< 0.1%
-2.099999905 2
< 0.1%
-2.094999933 1
< 0.1%
-2.087499917 1
< 0.1%
ValueCountFrequency (%)
35.84750042 1
< 0.1%
35.78947449 1
< 0.1%
35.61500034 1
< 0.1%
35.57058806 1
< 0.1%
35.40500011 1
< 0.1%
35.38684223 1
< 0.1%
35.27941132 1
< 0.1%
35.19999996 1
< 0.1%
35.06499996 1
< 0.1%
35.00000076 1
< 0.1%

Front bearing temperature (°C)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct38784
Distinct (%)74.6%
Missing714
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean65.865409
Minimum8.8999996
Maximum81.1275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:29:20.314345image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum8.8999996
5-th percentile41.3625
Q163.345592
median71.1025
Q372.732499
95-th percentile74.184999
Maximum81.1275
Range72.227501
Interquartile range (IQR)9.3869064

Descriptive statistics

Standard deviation11.801555
Coefficient of variation (CV)0.17917683
Kurtosis6.4322688
Mean65.865409
Median Absolute Deviation (MAD)2.4174999
Skewness-2.3968941
Sum3424342.6
Variance139.2767
MonotonicityNot monotonic
2023-07-08T17:29:20.534453image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.600000381 21
 
< 0.1%
23 21
 
< 0.1%
9.300000191 18
 
< 0.1%
9.5 18
 
< 0.1%
10.19999981 16
 
< 0.1%
19.89999962 15
 
< 0.1%
9.699999809 14
 
< 0.1%
22.89999962 14
 
< 0.1%
9.899999619 14
 
< 0.1%
73.99249954 14
 
< 0.1%
Other values (38774) 51825
98.3%
(Missing) 714
 
1.4%
ValueCountFrequency (%)
8.899999619 2
< 0.1%
8.902499628 1
 
< 0.1%
8.924999714 1
 
< 0.1%
8.939999771 1
 
< 0.1%
8.972499895 2
< 0.1%
8.992499971 1
 
< 0.1%
9 4
< 0.1%
9.005000019 1
 
< 0.1%
9.089999914 2
< 0.1%
9.109999943 1
 
< 0.1%
ValueCountFrequency (%)
81.12750015 1
< 0.1%
80.40249939 1
< 0.1%
80.37000046 1
< 0.1%
80.36750107 1
< 0.1%
80.36500053 1
< 0.1%
80.32499886 1
< 0.1%
80.3099987 1
< 0.1%
80.30749969 1
< 0.1%
80.25249939 1
< 0.1%
80.24749985 1
< 0.1%

Tower Acceleration X (mm/ss)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct51989
Distinct (%)> 99.9%
Missing714
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean52.987512
Minimum2.9004717
Maximum268.56941
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:29:20.635817image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.9004717
5-th percentile5.184523
Q134.702184
median51.11308
Q369.961501
95-th percentile102.00824
Maximum268.56941
Range265.66894
Interquartile range (IQR)35.259317

Descriptive statistics

Standard deviation28.376416
Coefficient of variation (CV)0.53553026
Kurtosis0.8723131
Mean52.987512
Median Absolute Deviation (MAD)17.549515
Skewness0.54061227
Sum2754820.7
Variance805.22099
MonotonicityNot monotonic
2023-07-08T17:29:20.734008image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.937859905 2
 
< 0.1%
46.37495341 1
 
< 0.1%
4.176372337 1
 
< 0.1%
4.460210148 1
 
< 0.1%
4.592716242 1
 
< 0.1%
4.463138482 1
 
< 0.1%
5.241938382 1
 
< 0.1%
4.905898482 1
 
< 0.1%
4.223244363 1
 
< 0.1%
4.410255212 1
 
< 0.1%
Other values (51979) 51979
98.6%
(Missing) 714
 
1.4%
ValueCountFrequency (%)
2.900471652 1
< 0.1%
2.970162189 1
< 0.1%
2.997387218 1
< 0.1%
3.089391047 1
< 0.1%
3.090064692 1
< 0.1%
3.115324995 1
< 0.1%
3.21961635 1
< 0.1%
3.257188439 1
< 0.1%
3.296176013 1
< 0.1%
3.338682711 1
< 0.1%
ValueCountFrequency (%)
268.5694099 1
< 0.1%
260.8127949 1
< 0.1%
241.2607216 1
< 0.1%
236.705378 1
< 0.1%
233.4448565 1
< 0.1%
225.82698 1
< 0.1%
221.3706005 1
< 0.1%
219.8193033 1
< 0.1%
218.9401339 1
< 0.1%
217.4649834 1
< 0.1%

Wind speed (m/s)
Real number (ℝ)

Distinct52133
Distinct (%)99.8%
Missing460
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean6.6771579
Minimum0.22188178
Maximum22.776431
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:29:20.834088image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.22188178
5-th percentile2.3619843
Q14.4679509
median6.3812004
Q38.4868092
95-th percentile12.111043
Maximum22.776431
Range22.554549
Interquartile range (IQR)4.0188583

Descriptive statistics

Standard deviation3.0249792
Coefficient of variation (CV)0.45303394
Kurtosis0.62024036
Mean6.6771579
Median Absolute Deviation (MAD)1.9868093
Skewness0.67529293
Sum348841.44
Variance9.150499
MonotonicityNot monotonic
2023-07-08T17:29:20.930064image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.619999886 3
 
< 0.1%
4.190000057 3
 
< 0.1%
1.190000057 3
 
< 0.1%
2.839999914 3
 
< 0.1%
4.03000021 3
 
< 0.1%
5.349999905 3
 
< 0.1%
3.710000038 3
 
< 0.1%
4.75 3
 
< 0.1%
5.03000021 3
 
< 0.1%
5.5 3
 
< 0.1%
Other values (52123) 52214
99.1%
(Missing) 460
 
0.9%
ValueCountFrequency (%)
0.2218817782 1
< 0.1%
0.2468627973 1
< 0.1%
0.2552439852 1
< 0.1%
0.2953126237 1
< 0.1%
0.3491053885 1
< 0.1%
0.3631501459 1
< 0.1%
0.3670658555 1
< 0.1%
0.3693376392 1
< 0.1%
0.370031346 1
< 0.1%
0.3812627066 1
< 0.1%
ValueCountFrequency (%)
22.77643118 1
< 0.1%
22.74410304 1
< 0.1%
22.58249993 1
< 0.1%
22.32538142 1
< 0.1%
22.29903755 1
< 0.1%
21.97199995 1
< 0.1%
21.84600177 1
< 0.1%
21.31282492 1
< 0.1%
21.2220561 1
< 0.1%
21.17223744 1
< 0.1%

Tower Acceleration y (mm/ss)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct51990
Distinct (%)100.0%
Missing714
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean28.824302
Minimum3.0858546
Maximum264.16008
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:29:21.025949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum3.0858546
5-th percentile5.4836115
Q117.076413
median25.269608
Q336.605565
95-th percentile61.695763
Maximum264.16008
Range261.07423
Interquartile range (IQR)19.529152

Descriptive statistics

Standard deviation18.280366
Coefficient of variation (CV)0.63419978
Kurtosis9.7419612
Mean28.824302
Median Absolute Deviation (MAD)9.3760065
Skewness2.0871965
Sum1498575.5
Variance334.17179
MonotonicityNot monotonic
2023-07-08T17:29:21.123282image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.54436457 1
 
< 0.1%
4.338487881 1
 
< 0.1%
4.725280106 1
 
< 0.1%
4.60007288 1
 
< 0.1%
5.068497495 1
 
< 0.1%
3.973814116 1
 
< 0.1%
4.391001379 1
 
< 0.1%
4.942070097 1
 
< 0.1%
5.347105932 1
 
< 0.1%
4.845856225 1
 
< 0.1%
Other values (51980) 51980
98.6%
(Missing) 714
 
1.4%
ValueCountFrequency (%)
3.08585465 1
< 0.1%
3.144935867 1
< 0.1%
3.165565234 1
< 0.1%
3.308651108 1
< 0.1%
3.377190828 1
< 0.1%
3.45965187 1
< 0.1%
3.463244474 1
< 0.1%
3.466163361 1
< 0.1%
3.471608484 1
< 0.1%
3.478344518 1
< 0.1%
ValueCountFrequency (%)
264.16008 1
< 0.1%
248.4000547 1
< 0.1%
234.5682426 1
< 0.1%
231.3489014 1
< 0.1%
219.3462609 1
< 0.1%
212.0520244 1
< 0.1%
206.5839756 1
< 0.1%
203.4798036 1
< 0.1%
203.0081169 1
< 0.1%
202.001153 1
< 0.1%
Distinct23
Distinct (%)< 0.1%
Missing714
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean519.31468
Minimum510
Maximum532
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:29:21.212186image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum510
5-th percentile511
Q1515
median519
Q3526
95-th percentile529
Maximum532
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.0392261
Coefficient of variation (CV)0.011629223
Kurtosis-1.1095824
Mean519.31468
Median Absolute Deviation (MAD)4
Skewness0.35729888
Sum26999170
Variance36.472252
MonotonicityIncreasing
2023-07-08T17:29:21.290580image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
515 14912
28.3%
519 9095
17.3%
526 5342
 
10.1%
528 5181
 
9.8%
511 3513
 
6.7%
523 2620
 
5.0%
510 2142
 
4.1%
514 1964
 
3.7%
530 1828
 
3.5%
524 1329
 
2.5%
Other values (13) 4064
 
7.7%
ValueCountFrequency (%)
510 2142
 
4.1%
511 3513
 
6.7%
512 33
 
0.1%
513 939
 
1.8%
514 1964
 
3.7%
515 14912
28.3%
516 80
 
0.2%
517 30
 
0.1%
518 855
 
1.6%
519 9095
17.3%
ValueCountFrequency (%)
532 706
 
1.3%
531 47
 
0.1%
530 1828
 
3.5%
529 508
 
1.0%
528 5181
9.8%
527 59
 
0.1%
526 5342
10.1%
525 516
 
1.0%
524 1329
 
2.5%
523 2620
5.0%

Interactions

2023-07-08T17:29:16.643819image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:02.480363image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:03.604641image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:04.800781image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:05.975173image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:07.201349image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:08.380824image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:09.563689image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:10.840991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:12.015243image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:13.191217image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:14.440739image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:15.527915image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:16.721997image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:02.555929image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:03.690357image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:04.884838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:06.055294image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:07.287170image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:08.468087image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:09.646189image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:10.925810image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:12.099752image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:13.271399image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:14.519140image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:15.606234image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:16.810381image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:02.642964image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:03.782928image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:04.978033image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:06.144008image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:07.378157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:08.561635image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:09.739543image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:11.018962image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:12.191838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:13.359086image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:14.605047image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:15.695154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:16.898242image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:02.733303image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:03.875395image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:05.072452image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:06.237067image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:07.472839image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:08.656219image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:09.830464image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:11.114839image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:12.287460image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:13.449555image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:14.692076image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:15.783675image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:16.976147image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:02.815669image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:03.958154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:05.157400image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:06.315959image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:07.555761image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:08.740662image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:09.914517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:11.199477image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:12.369803image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:13.530851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:14.769431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:15.865311image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:17.067108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:02.906957image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:04.054862image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:05.251256image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:06.522232image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:07.649260image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:08.834373image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:10.007266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:11.293571image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:12.463250image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:13.625423image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:14.857979image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:15.954732image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:17.156472image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:02.999711image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:04.152542image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:05.344517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:06.611133image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:07.743302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:08.932364image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:10.218218image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:11.388973image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:12.558169image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:13.719821image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:14.946385image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:16.048010image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:17.244573image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:03.091129image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:04.245945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:05.441009image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:06.697901image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:07.839194image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:09.024403image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:10.306096image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:11.483153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:12.654560image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:13.810214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:15.034247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:16.135897image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:17.332719image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:03.181311image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:04.342812image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:05.533241image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:06.788249image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:07.934000image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:09.120318image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:10.400289image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:11.574294image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:12.746108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:13.901275image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:15.120978image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:16.225940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:17.421835image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:03.271453image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:04.442856image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:05.628700image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:06.876770image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:08.031007image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:09.214463image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:10.492438image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:11.669859image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:12.840370image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:13.992891image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:15.207578image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:16.316024image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:17.503973image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:03.355808image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:04.533516image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:05.715839image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:06.959526image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:08.121413image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:09.304705image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:10.580642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:11.756679image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:12.928412image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:14.189975image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:15.289890image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:16.397596image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:17.581961image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:03.435717image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:04.621314image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:05.800577image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:07.039622image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:08.207031image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:09.388477image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:10.663172image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:11.842412image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:13.013167image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:14.272067image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:15.366379image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:16.480070image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:17.664493image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:03.520457image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:04.710162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:05.889302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:07.121440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:08.293699image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:09.475864image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:10.754283image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:11.929077image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:13.101672image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:14.356391image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:15.449643image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:29:16.561048image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-07-08T17:29:21.370618image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Power (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
Power (kW)1.0000.0160.002-0.0940.5790.9920.992-0.1990.8540.6340.9510.827-0.105
Wind direction (°)0.0161.0000.9290.070-0.0490.0130.014-0.106-0.0120.1010.0290.0680.041
Nacelle position (°)0.0020.9291.0000.078-0.061-0.002-0.000-0.107-0.0240.0960.0210.0610.046
blade_angle-0.0940.0700.0781.000-0.530-0.109-0.1100.033-0.2720.034-0.0220.069-0.054
Rear bearing temperature (°C)0.579-0.049-0.061-0.5301.0000.5780.5710.1320.7950.3010.5260.3860.029
Rotor speed (RPM)0.9920.013-0.002-0.1090.5781.0000.999-0.1940.8540.6260.9420.818-0.100
Generator RPM (RPM)0.9920.014-0.000-0.1100.5710.9991.000-0.2110.8530.6260.9410.818-0.106
Nacelle ambient temperature (°C)-0.199-0.106-0.1070.0330.132-0.194-0.2111.000-0.115-0.161-0.185-0.1610.131
Front bearing temperature (°C)0.854-0.012-0.024-0.2720.7950.8540.853-0.1151.0000.4970.8020.662-0.092
Tower Acceleration X (mm/ss)0.6340.1010.0960.0340.3010.6260.626-0.1610.4971.0000.5780.840-0.113
Wind speed (m/s)0.9510.0290.021-0.0220.5260.9420.941-0.1850.8020.5781.0000.826-0.075
Tower Acceleration y (mm/ss)0.8270.0680.0610.0690.3860.8180.818-0.1610.6620.8400.8261.000-0.123
Metal particle count counter-0.1050.0410.046-0.0540.029-0.100-0.1060.131-0.092-0.113-0.075-0.1231.000

Missing values

2023-07-08T17:29:17.783312image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-07-08T17:29:17.981790image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-07-08T17:29:18.327840image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

# Date and timePower (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
02020-01-01 00:00:00478.404070113.777843102.7328030.00000073.31749911.3708811347.3974306.78250073.80999846.3749536.00068824.544365510.0
12020-01-01 00:10:00367.411460112.494372102.7328030.00000069.59000010.5194971246.3357606.71000070.35000035.2815025.51073118.475142510.0
22020-01-01 00:20:00361.421001115.418801102.7328030.00000068.54750010.4087461233.7004366.72000068.97500040.4462625.14440020.396388510.0
32020-01-01 00:30:00143.825712110.707508102.7328030.07349966.3025008.387016993.4669286.61750066.64500062.4334953.87934726.873033510.0
42020-01-01 00:40:00169.296115115.023328102.7328030.04916665.8175008.6219711022.3453416.52000065.39250059.7543274.15422029.637973510.0
52020-01-01 00:50:00318.590322123.193735112.6101820.00000068.0222239.9836081184.2720866.67777867.61111235.2886335.24295816.181514510.0
62020-01-01 01:00:00431.298383131.006684130.1717380.00000069.98000010.9944351303.4349126.77250069.97500036.9179245.70309422.029387510.0
72020-01-01 01:10:00413.775522131.901442130.1717380.00000070.94750110.9254471295.3581186.73750071.48000148.4955325.82792622.870779510.0
82020-01-01 01:20:00363.646341128.214481130.1717380.00000070.42500110.4896391242.9597646.77250071.06249945.1654875.58607620.458193510.0
92020-01-01 01:30:00364.748104136.388574130.1717380.00000070.88000010.4755001241.1634716.79750071.42250149.7671655.57727718.995982510.0
# Date and timePower (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
526942020-12-31 22:20:00-1.298539307.767471317.85424889.98999810.29500.0-0.6704110.50009.65255.5834025.8946638.547565532.0
526952020-12-31 22:30:00-1.431914308.968263317.85424889.98999810.06500.0-0.6883540.67009.60005.6570506.0878444.970305532.0
526962020-12-31 22:40:00-2.913444299.389345317.85424889.9899989.90000.0-0.4136860.83009.55005.8967995.2795697.690257532.0
526972020-12-31 22:50:00-1.476195299.195112317.85424889.9899989.83250.0-0.6956800.89759.42507.1611644.9962005.014988532.0
526982020-12-31 23:00:00-4.270134299.804569317.85424889.9899989.66250.0-0.6570530.96259.29255.5809324.9551755.513235532.0
526992020-12-31 23:10:00-5.659902299.981742317.85424889.9899989.79000.0-0.6460421.00009.20254.6351284.8911444.597098532.0
527002020-12-31 23:20:00-2.613083300.550618317.85424889.9899989.94000.0-0.6707841.00509.20004.2375874.7535944.690982532.0
527012020-12-31 23:30:00-2.400750297.611820317.85424889.9899989.63500.0-0.7163651.00009.11004.3506414.5579564.142608532.0
527022020-12-31 23:40:00-3.003605294.617002317.56218289.9899989.40500.0-0.7102671.07009.00004.1717134.1643374.598473532.0
527032020-12-31 23:50:00-3.341311300.983100291.74625389.9899989.44750.0-0.4258380.95009.00004.6043674.7599505.226698532.0